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Data Science Toolbox","Deep Learning","Python","Tensor Flow"],"sub_categories":["Deep Learning Packages","TensorFlow","Automated Machine Learning"],"readme":"# keras-contrib : Keras community contributions\n\nKeras-contrib is deprecated. Use [TensorFlow Addons](https://github.com/tensorflow/addons).\n\n## The future of Keras-contrib:\n\nWe're migrating to [tensorflow/addons](https://github.com/tensorflow/addons). See the announcement [here](https://github.com/keras-team/keras-contrib/issues/519). \n\n[![Build Status](https://travis-ci.org/keras-team/keras-contrib.svg?branch=master)](https://travis-ci.org/keras-team/keras-contrib)\n\nThis library is the official extension repository for the python deep learning library [Keras](http://www.keras.io). It contains additional layers, activations, loss functions, optimizers, etc. which are not yet available within Keras itself. All of these additional modules can be used in conjunction with core Keras models and modules.\n\nAs the community contributions in Keras-Contrib are tested, used, validated, and their utility proven, they may be integrated into the Keras core repository. In the interest of keeping Keras succinct, clean, and powerfully simple, only the most useful contributions make it into Keras. This contribution repository is both the proving ground for new functionality, and the archive for functionality that (while useful) may not fit well into the Keras paradigm.\n\n\n\n\n\n---\n## Installation\n\n#### Install keras_contrib for keras-team/keras\nFor instructions on how to install Keras, \nsee [the Keras installation page](https://keras.io/#installation).\n\n```shell\ngit clone https://www.github.com/keras-team/keras-contrib.git\ncd keras-contrib\npython setup.py install\n```\n\nAlternatively, using pip:\n\n```shell\nsudo pip install git+https://www.github.com/keras-team/keras-contrib.git\n```\n\nto uninstall:\n```pip\npip uninstall keras_contrib\n```\n\n#### Install keras_contrib for tensorflow.keras\n\n```shell\ngit clone https://www.github.com/keras-team/keras-contrib.git\ncd keras-contrib\npython convert_to_tf_keras.py\nUSE_TF_KERAS=1 python setup.py install\n```\n\nto uninstall:\n```shell\npip uninstall tf_keras_contrib\n```\n\nFor contributor guidelines see [CONTRIBUTING.md](https://github.com/keras-team/keras-contrib/blob/master/CONTRIBUTING.md)\n\n---\n## Example Usage\n\nModules from the Keras-Contrib library are used in the same way as modules within Keras itself.\n\n```python\nfrom keras.models import Sequential\nfrom keras.layers import Dense\nimport numpy as np\n\n# I wish Keras had the Parametric Exponential Linear activation..\n# Oh, wait..!\nfrom keras_contrib.layers.advanced_activations import PELU\n\n# Create the Keras model, including the PELU advanced activation\nmodel = Sequential()\nmodel.add(Dense(100, input_shape=(10,)))\nmodel.add(PELU())\n\n# Compile and fit on random data\nmodel.compile(loss='mse', optimizer='adam')\nmodel.fit(x=np.random.random((100, 10)), y=np.random.random((100, 100)), epochs=5, verbose=0)\n\n# Save our model\nmodel.save('example.h5')\n```\n\n\n### A Common \"Gotcha\"\n\nAs Keras-Contrib is external to the Keras core, loading a model requires a bit more work. While a pure Keras model is loadable with nothing more than an import of `keras.models.load_model`, a model which contains a contributed module requires an additional import of `keras_contrib`:\n\n```python\n# Required, as usual\nfrom keras.models import load_model\n\n# Recommended method; requires knowledge of the underlying architecture of the model\nfrom keras_contrib.layers import PELU\nfrom keras_contrib.layers import GroupNormalization\n\n# Load our model\ncustom_objects = {'PELU': PELU, 'GroupNormalization': GroupNormalization}\nmodel = load_model('example.h5', custom_objects)\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkeras-team%2Fkeras-contrib","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkeras-team%2Fkeras-contrib","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkeras-team%2Fkeras-contrib/lists"}